Determining gaps in data

ABSTRACT

Examples of techniques for performing a skill gap comparison between a first individual and a second individual (or group) are disclosed. In one example, a computer-implemented method includes receiving first data associated with the first individual and receiving second data associated with the second individual. The method further includes identifying preferences for performing the skill gap comparison and assigning a weight for each of a plurality of elements of the first data and the second data. The method further includes performing the skill gap comparison between the first individual and the second individual by comparing the first data to the second data. The method further includes generating a list of one or more skills for which there is a skill gap between the first individual and the second individual.

BACKGROUND

The present invention generally relates to data processing system, andmore specifically, to determining gaps in data.

Data are collected in a variety of ways from various sources. It may bedesirable to analyze the data to extract meaningful information from thedata. For example, in data analysis, it may be desirable to compare datasets to determine differences in the data. In one such example, dataassociated with a first individual can be compared to data associatedwith a second individual (or group) to determine differences or gaps ordifferences between the data.

SUMMARY

Embodiments of the present invention are directed to acomputer-implemented method for performing a skill gap comparisonbetween a first individual and a second individual. A non-limitingexample of the computer-implemented method includes receiving, by aprocessing device, first data associated with the first individual. Themethod further includes receiving, by the processing device, second dataassociated with the second individual. The method further includesidentifying, by the processing device, preferences for performing theskill gap comparison. The method further includes assigning, by theprocessing device, a weight for each of a plurality of elements of thefirst data and the second data. The method further includes performing,by the processing device, the skill gap comparison between the firstindividual and the second individual by comparing the first data to thesecond data based at least in part on the preferences identified forperforming the skill gap comparison and the weight assigned for each ofthe plurality of elements of the first data and the second data. Themethod further includes generating, by the processing device, a list ofone or more skills for which there is a skill gap between the firstindividual and the second individual.

Embodiments of the present invention are directed to a system. Anon-limiting example of the system includes a memory comprising computerreadable instructions and a processing device for executing the computerreadable instructions for performing a method for performing a skill gapcomparison between a first individual and a second individual.

Embodiments of the invention are directed to a computer program product.A non-limiting example of the computer program product includes acomputer readable storage medium having program instructions embodiedtherewith. The program instructions are executable by a processor tocause the processor to perform a method for performing a skill gapcomparison between a first individual and a second individual.

Additional technical features and benefits are realized through thetechniques of the present invention. Embodiments and aspects of theinvention are described in detail herein and are considered a part ofthe claimed subject matter. For a better understanding, refer to thedetailed description and to the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The specifics of the exclusive rights described herein are particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The foregoing and other features and advantages ofthe embodiments of the invention are apparent from the followingdetailed description taken in conjunction with the accompanying drawingsin which:

FIG. 1 depicts a cloud computing environment according to aspects of thepresent disclosure;

FIG. 2 depicts abstraction model layers according to aspects of thepresent disclosure;

FIG. 3 depicts a block diagram of a processing system for implementingthe techniques described herein according to aspects of the presentdisclosure;

FIG. 4 depicts a block diagram of a processing system for performing askill gap comparison according to one or more embodiments of the presentinvention;

FIG. 5 depicts a flow diagram of a method for performing a skill gapcomparison between a first individual and a second individual (or group)according to one or more embodiments of the present invention; and

FIG. 6 depicts a flow diagram of a method for performing a skill gapcomparison between a first individual and a second individual (or group)according to one or more embodiments of the present invention.

The diagrams depicted herein are illustrative. There can be manyvariations to the diagram or the operations described therein withoutdeparting from the spirit of the invention. For instance, the actionscan be performed in a differing order or actions can be added, deletedor modified. Also, the term “coupled” and variations thereof describeshaving a communications path between two elements and does not imply adirect connection between the elements with no interveningelements/connections between them. All of these variations areconsidered a part of the specification.

In the accompanying figures and following detailed description of thedisclosed embodiments, the various elements illustrated in the figuresare provided with two or three digit reference numbers. With minorexceptions, the leftmost digit(s) of each reference number correspondsto the figure in which its element is first illustrated.

DETAILED DESCRIPTION

Various embodiments of the invention are described herein with referenceto the related drawings. Alternative embodiments of the invention can bedevised without departing from the scope of this invention. Variousconnections and positional relationships (e.g., over, below, adjacent,etc.) are set forth between elements in the following description and inthe drawings. These connections and/or positional relationships, unlessspecified otherwise, can be direct or indirect, and the presentinvention is not intended to be limiting in this respect. Accordingly, acoupling of entities can refer to either a direct or an indirectcoupling, and a positional relationship between entities can be a director indirect positional relationship. Moreover, the various tasks andprocess steps described herein can be incorporated into a morecomprehensive procedure or process having additional steps orfunctionality not described in detail herein.

The following definitions and abbreviations are to be used for theinterpretation of the claims and the specification. As used herein, theterms “comprises,” “comprising,” “includes,” “including,” “has,”“having,” “contains” or “containing,” or any other variation thereof,are intended to cover a non-exclusive inclusion. For example, acomposition, a mixture, process, method, article, or apparatus thatcomprises a list of elements is not necessarily limited to only thoseelements but can include other elements not expressly listed or inherentto such composition, mixture, process, method, article, or apparatus.

Additionally, the term “exemplary” is used herein to mean “serving as anexample, instance or illustration.” Any embodiment or design describedherein as “exemplary” is not necessarily to be construed as preferred oradvantageous over other embodiments or designs. The terms “at least one”and “one or more” may be understood to include any integer numbergreater than or equal to one, i.e. one, two, three, four, etc. The terms“a plurality” may be understood to include any integer number greaterthan or equal to two, i.e. two, three, four, five, etc. The term“connection” may include both an indirect “connection” and a direct“connection.”

The terms “about,” “substantially,” “approximately,” and variationsthereof, are intended to include the degree of error associated withmeasurement of the particular quantity based upon the equipmentavailable at the time of filing the application. For example, “about”can include a range of ±8% or 5%, or 2% of a given value.

For the sake of brevity, conventional techniques related to making andusing aspects of the invention may or may not be described in detailherein. In particular, various aspects of computing systems and specificcomputer programs to implement the various technical features describedherein are well known. Accordingly, in the interest of brevity, manyconventional implementation details are only mentioned briefly herein orare omitted entirely without providing the well-known system and/orprocess details.

It is to be understood that, although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 1, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 1 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 2, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 1) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 2 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and comparing skill gaps between individualsor groups 96.

It is understood that the present disclosure is capable of beingimplemented in conjunction with any other type of computing environmentnow known or later developed. For example, FIG. 3 depicts a blockdiagram of a processing system 300 for implementing the techniquesdescribed herein. In examples, processing system 300 has one or morecentral processing units (processors) 321 a, 321 b, 321 c, etc.(collectively or generically referred to as processor(s) 321 and/or asprocessing device(s)). In aspects of the present disclosure, eachprocessor 321 can include a reduced instruction set computer (RISC)microprocessor. Processors 321 are coupled to system memory (e.g.,random access memory (RAM) 324) and various other components via asystem bus 333. Read only memory (ROM) 322 is coupled to system bus 333and may include a basic input/output system (BIOS), which controlscertain basic functions of processing system 300.

Further depicted are an input/output (I/O) adapter 327 and acommunications adapter 326 coupled to system bus 333. I/O adapter 327may be a small computer system interface (SCSI) adapter thatcommunicates with a hard disk 323 and/or a tape storage drive 325 or anyother similar component. I/O adapter 327, hard disk 323, and tapestorage device 325 are collectively referred to herein as mass storage334. Operating system 340 for execution on processing system 300 may bestored in mass storage 334. A network adapter 326 interconnects systembus 333 with an outside network 336 enabling processing system 300 tocommunicate with other such systems.

A display (e.g., a display monitor) 335 is connected to system bus 333by display adaptor 332, which may include a graphics adapter to improvethe performance of graphics intensive applications and a videocontroller. In one aspect of the present disclosure, adapters 326, 327,and/or 232 may be connected to one or more I/O busses that are connectedto system bus 333 via an intermediate bus bridge (not shown). SuitableI/O buses for connecting peripheral devices such as hard diskcontrollers, network adapters, and graphics adapters typically includecommon protocols, such as the Peripheral Component Interconnect (PCI).Additional input/output devices are shown as connected to system bus 333via user interface adapter 328 and display adapter 332. A keyboard 329,mouse 330, and speaker 331 may be interconnected to system bus 333 viauser interface adapter 328, which may include, for example, a Super I/Ochip integrating multiple device adapters into a single integratedcircuit.

In some aspects of the present disclosure, processing system 300includes a graphics processing unit 337. Graphics processing unit 337 isa specialized electronic circuit designed to manipulate and alter memoryto accelerate the creation of images in a frame buffer intended foroutput to a display. In general, graphics processing unit 337 is veryefficient at manipulating computer graphics and image processing, andhas a highly parallel structure that makes it more effective thangeneral-purpose CPUs for algorithms where processing of large blocks ofdata is done in parallel.

Thus, as configured herein, processing system 300 includes processingcapability in the form of processors 321, storage capability includingsystem memory (e.g., RAM 324), and mass storage 334, input means such askeyboard 329 and mouse 330, and output capability including speaker 331and display 335. In some aspects of the present disclosure, a portion ofsystem memory (e.g., RAM 324) and mass storage 334 collectively store anoperating system such as the AIX® operating system from IBM Corporationto coordinate the functions of the various components shown inprocessing system 300.

Turning now to an overview of technologies that are more specificallyrelevant to aspects of the invention, a person in a particular role(such as a job) may desire to gain knowledge and/or skills to transitioninto a different role (referred to as a “target role”) or to grow in hisor her current role. The target role is a role or position that a userwishes to obtain. A target role can also refer to obtaining the skillsand knowledge useful to perform a current role more efficiently andeffectively. There are no existing efficient mechanisms to facilitateidentifying and acquiring knowledge and skills for a different jobposition based on a peer-to-peer comparison of roles. Traditionally, ifa person wants to understand and/or obtain knowledge that will enablethe person to develop the skills required to transition into anotherrole, the person must manually search for general job role educationinformation. However, this general job role education information oftenlacks specific information useful for transitioning into the targetrole, such as the day-to-day knowledge and skills used to performfunctions of the target role and/or to effectively build and maintainrelationships associated with the target role (e.g., direct reports,managers, etc.).

Existing approaches fail to provide an efficient mechanism to identifyand acquire knowledge and skills for a target role. For example,existing approaches do not provide a peer-to-peer comparison to identifyknowledge and skills gaps, do not identify supplementary skill gaps fora future role, do not utilize unstructured profile data (e.g., socialnetworking data, email data, chat history data, and the like) to createa tailored skill gap list, and more.

Turning now to an overview of the aspects of the invention, one or moreembodiments of the invention address the above-described shortcomings ofthe prior art by providing an efficient mechanism to identify andacquire knowledge and skills for a target role by identifying a skillgap between two individuals. One or more embodiments of the presentinvention scan and identify individual or group of individuals' digitalprofile data (i.e., data collected about and pertaining to an individualor group of individuals' education, skills, etc.) and determine skillsgaps to enhance a person's education for growth towards a target role.The present techniques receive unstructured information in the form ofthe digital profile data from two individuals (Person A and Person B (orgroup)) and perform a peer-to-peer comparison to compare theunstructured information to determine skills gaps for Person A relativeto Person B (or group). A skills gap is a difference in skills between afirst individual (e.g., Person A) and a second individual (e.g., PersonB (or group)).

The above-described aspects of the invention address the shortcomings ofthe prior art in several ways. For example, the prior art fails toaddress peer-to-peer comparisons for identifying skill gaps. Further,the prior art does not address identifying supplementary skill gapsbased on day-to-day activities for a target job role. Additionally, theprior art does not address dealing with unstructured data forindividuals that can be used for performing peer-to-peer skill gapcomparisons.

Turning now to a more detailed description of aspects of the presentinvention, FIG. 4 depicts a block diagram of a processing system 400 forperforming a skill gap comparison according to one or more embodimentsof the present invention. The processing system 400 includes aprocessing device 402, a memory 404, a data engine 410 for receivingdata from and/or transmitting data to a database 406, and a skill gapengine 412 for performing a skill gap comparison.

The various components, modules, engines, etc. described regarding FIG.4 can be implemented as instructions stored on a computer-readablestorage medium, as hardware modules, as special-purpose hardware (e.g.,application specific hardware, application specific integrated circuits(ASICs), application specific special processors (ASSPs), fieldprogrammable gate arrays (FPGAs), as embedded controllers, hardwiredcircuitry, etc.), or as some combination or combinations of these.According to aspects of the present disclosure, the engine(s) describedherein can be a combination of hardware and programming. The programmingcan be processor executable instructions stored on a tangible memory,and the hardware can include the processing device 402 for executingthose instructions. Thus a system memory (e.g., memory 404) can storeprogram instructions that when executed by the processing device 402implement the engines described herein. Other engines can also beutilized to include other features and functionality described in otherexamples herein.

The data engine 410 receives data from a database 406, which canrepresent one or more databases or other data stores for storing data.Data can be associated with different individuals. Thus, the data engine410 can receive first data associated with a first individual, seconddata associated with a second individual, and so forth.

The data can include, but is not limited to, email data, chat historydata, education data, calendar data, social network data, text messagedata, meeting transcript data, and other suitable data. The data may bestructured (e.g., highly organized data), semi-structured (e.g.,unstructured data that contains tags or information to define semanticelements and enforce hierarchies of records and fields within the data),and/or unstructured (e.g., unorganized data or data without a defineddata model).

Once the data are received by the data engine 410, the skill gap engine412 can begin the process of comparing data between individuals todetermine a skill gap. The data engine 410 first enables theidentification of preferences for performing the skill gap comparison.Next, the data engine 410 assigns a weight to elements of the first andsecond data. The elements can include words and/or phrases extractedfrom the data. These elements can be assigned a weight, for example,based on the identified preferences for performing the skill gap. Theextraction can be performed using a content analysis API or anothersuitable platform for performing such an extraction. The weighting canbe performed using a retrieve and rank API 422 or another suitableplatform for performing such a weighting. The skill gap engine 412 canperform a skill gap comparison between the first individual and thesecond individual by comparing the first data and the second data usingthe identified preferences and weighting of elements.

FIG. 5 depicts a flow diagram of a method 500 for performing a skill gapcomparison between a first individual and a second individual (or group)according to one or more embodiments of the present invention. Themethod 500 can be performed using any suitable processing device (e.g.,the CPU 321, the processing device 402) and/or processing system (e.g.,the processing system 300, the processing system 400) or suitablecombinations thereof.

At block 502, the data engine 410 receives first data associated with afirst individual. At block 504, the data engine 410 receives second dataassociated with a second individual (or group). The first dataassociated with the first individual and/or the second data associatedwith the second individual (or group) can be structured data,semi-structured data, and/or unstructured data. Examples of unstructureddata can include one or more of email data, chat history data, educationtranscript data, calendar data, social media data, role descriptiondata, resume data, and the like.

At block 506, the skill gap engine 412 identifies preferences forperforming the skill gap comparison. Preferences enable the skill gapcomparison to be limited to specific search fields, time periods, etc.,and/or focused on particular topics such as formal education type.Examples of preferences can include a time period (e.g., a number ofdays) for which to search the first data and the second data, fields tobe searched (e.g., subject of emails, body of chat history), types ofdata to be searched (e.g., email, chats, social networks, meetingtranscripts, resumes, etc.), education type (including related articles,web links, informal education, formal education, etc.), a language,search results limit (e.g., 5 results, 10 results, 25 results, etc.),and others.

At block 508, the skill gap engine 412 assigns a weight for each of aplurality of elements of the first data and the second data. Theplurality of elements of the first data and the second data can wordsand phrases associated with skills. Words and phrases can be detectedthat are indicative of skills. For example, the skill gap engine 412 cananalyze words and phrases detected in the second individual's chathistory data to determine soft skills that the second individual may usewhen performing functions of his role. Such soft skills can includeparticular topics the second individual discusses with his or her directreports and/or with his or her supervisor. Assigning the weight at block508 can be performed using a cognitive exploration and content analysisplatform such as a content analysis API (e.g., content analysis API 420)or another suitable platform.

At block 510, the skill gap engine 412 performs the skill gap comparisonbetween the first individual and the second individual (or group) todetermine a skill gap. The skill gap comparison is performed bycomparing the first data to the second data based at least in part onthe preferences identified for performing the skill gap comparison atblock 506 and/or the weight assigned for each of the plurality ofelements of the first data and the second data at block 508.

Performing the skill gap comparison can include identifying skills forthe first individual from the first data associated with the firstindividual. Performing the skill gap comparison can also includeidentifying skills for the from the second data associated with thesecond individual. By using the preferences and ranking to perform theskill gap comparison, processing resources are reduced and the searchcan be performed more expeditiously than in the prior art. For example,the search can be limited to certain time periods, certain subjects,etc., which reduces search time and increases efficiency. Similarly, byperforming the skill gap comparison using the weight of the elements ofthe first and second data, higher weighted elements can be searchedwithout spending processing resources and time to search for lowerweight elements.

According to one or more embodiments of the present invention, thesecond individual (or group) can represent a group of individuals andthe second data can represent data associated with the group ofindividuals. This enables the skill gap comparison at block 510 to beperformed by comparing the first person to a group of individuals.

At block 512, the skill gap engine 412 generates a list of one or moreskills for which there is a skill gap, as determined at block 510,between the first individual and the second individual.

Additional processes also may be included. For example, according to oneor more embodiments of the present invention, the skill gap engine 412can update the list of one or more skills in real-time when at least oneof new first data associated with the first individual and new seconddata associated with the second individual (or group) are received. Byupdating the list of skills in real-time, the present techniques canaccount for changes in individual's skills. For example, if the secondindividual (or group) develops a new skill, it can be determined and canbe added to the list of skills for which there is a skill gap. Thisenables the first individual to seek additional training or knowledge todevelop the new skill.

As another example, according to one or more embodiments of the presentinvention, the skill gap engine 412 can generate a list of a pluralityof skilled individuals. The skilled individuals each have at least oneof the skills of the list of the one or more skills for which there is askill gap between the first individual and the second individual. Byidentifying the skilled individuals that have one of the skill gapskills, the first individual (or the second individual) can performskill gap comparisons with that skilled individual, can seek training ormentorship from that skilled individual, etc. The skill gap engine 412can rank the plurality of skilled individuals based at least in part ona skill level of the at least one of the skills of the list of one ormore skills. For example, a highly skilled individual (e.g., a skilllevel of 9 on a scale of 1-10) can be ranked higher than a less skilledindividual (e.g., a skill level of 5 on a scale of 1-10). Performing theranking can be performed using a retrieve and rank platform such as aretrieve and rank API (e.g., the retrieve and rank API 422) or anothersuitable platform.

It should be understood that the process depicted in FIG. 5 representsan illustration, and that other processes may be added or existingprocesses may be removed, modified, or rearranged without departing fromthe scope and spirit of the present disclosure.

FIG. 6 depicts a flow diagram of a method 600 for performing a skill gapcomparison between a first individual and a second individual (or group)according to one or more embodiments of the present invention. Themethod 500 can be performed using any suitable processing device (e.g.,the CPU 321, the processing device 402) and/or processing system (e.g.,the processing system 300, the processing system 400) or suitablecombinations thereof. The method 600 is now described with reference toblocks 620, 622 a, 622 b, 622 c, 622 d, 622 e, 622 f, 623, 624, 626,627, 632 a, 632 b, 634, and steps 601, 602 a, 602 b, 602 c, 602 d, 602e, 602 f, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612 a, 612 b,613, 614.

The method 600 begins at block 620, where a skill gap comparison betweenPerson A and Person B (or group) is initiated. That is, a comparison ofPerson A to Person B (or group) is desired such that a skill gap betweenPerson A and Person B (or group) is determined. This is useful, forexample, when Person A wants to determine what skills he or she needs toacquire to perform a target role performed by Person B. At step 601, themethod 600 proceeds initiate the skill gap comparison process on theprocessing system 400.

The processing system 400 obtains or receives data from various datasources for each of the individuals (e.g., Person A and Person B (orgroup)) to generate a digital profile for each of the individuals. Forexample, at step 602 a, the processing system 400 receives data from anemail data source 622 a. Similarly, at step 602 b, the processing system400 receives data from a chat history data source 622 b. At step 602 c,the processing system 400 receives data from an education data source622 c. At step 602 d, the processing system 400 receives data from acalendar data source 622 d. At step 602 e, the processing system 400receives data from a social network data source 622 e. At step 602 c,the processing system 400 receives data from other digital data sources622 f.

Once the data is received from the various sources 622 a-622 f, theprocessing system 400 initiates step 603, which feeds the data into thecontent analysis API 623 or another suitable API. The content analysisAPI 623 or another suitable API extracts elements, such as words and/orphrases, from the data received in steps 602 a-602 f. Using theextracted elements, a list of words and phrases 624 is created at step604 and is sent back to the processing system 400 at step 605. It shouldbe appreciated that the elements can be extracted for one or both of theindividuals (e.g., Person A, Person B (or group)).

At step 606, the elements (i.e., the list of words and phrases 624) arefed into the retrieve and rank API 626 or another suitable API. Theretrieve and rank API 626 or another suitable API assigns weights foreach of the elements of the first data and the second data. In someexamples, the retrieve and rank API 626 generates, at step 607, a “top10” list 627 (or other ranking, such as a “top 5” list or a “highestpriority” list) of the elements, which are fed back into the processingsystem 400 at step 608. According to one or more embodiments of thepresent invention, the steps 606, 607, 608 can be repeated/iterated(labeled steps 609, 610, 611 respectively) to update the list 627 basedon changes to the data 622 a-622 f. This provides for real-time (or nearreal-time) updates to the list 627. By using the list 627, which mayinclude less than all of the elements from the list of words and phrases624, performing updates to the list 627 improves the functioning of theprocessing system 400 by reducing the amount of processing, memory,storage, and/or power resources that the processing system 400 utilizes.For example, by only updating the “top 10” elements from the list 627,the processing system 400 need not waste resources updating non-top 10elements. It should be appreciated that the list 627 can be generatedfor one or both of the individuals (e.g., Person A, Person B (orgroup)).

The processing system 400 then performs a skill gap comparison betweenPerson A and Person B. At step 612 a, a master skill list 632 a forPerson A is generated. The master skill list 632 a represents a list oftop skills that Person A possesses. Similarly, at step 612 b, a masterskill list 632 b for Person B is generated. The master skill list 632 brepresents a list of top skills that Person B possesses. At step 613,the processing system 400 compares the lists 632 a, 632 b to generate,at step 614, a master skill gap list 634 that represents a list ofskills for which there is a skill gap between Person A and Person B. Themaster skill gap list 634 includes skills (or knowledge) that Person Bpossesses that Person A does not possess. Person A, therefore, may wishto acquire or develop the skills included in the master skill gap list634 if Person A desires to be more like Person B (e.g., to obtain a jobsimilar to that of Person B).

Additional processes also may be included, and it should be understoodthat the process depicted in FIG. 6 represents an illustration and thatother processes may be added or existing processes may be removed,modified, or rearranged without departing from the scope and spirit ofthe present disclosure.

The present techniques can be implemented in a variety of different usecases. As one example, an individual would like to take on the role of aspecific person and take over their job duties (e.g., the user isseeking a promotion into another role). In another example, anindividual would like to gain skills and knowledge for a specific role(e.g., system programmer, accountant, sales manager, etc.). In yetanother example, an individual such as a supervisor or manager wouldlike to determine missing skills from within their team or department sothat additional team members can be hired to fill the skills gap, thatadditional training of existing team members can be performed, etc. Asanother example, an individual would like to prepare for a client visitand needs to understand the client's cultural needs, discussion topics,required skills, and the like.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instruction by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdescribed herein.

What is claimed is:
 1. A computer-implemented method for performing askill gap comparison between a first individual and a second individual,the method comprising: receiving, by a processing device, first dataassociated with the first individual; receiving, by the processingdevice, second data associated with the second individual; identifying,by the processing device, preferences for performing the skill gapcomparison; assigning, by the processing device, a weight for each of aplurality of elements of the first data and the second data; performing,by the processing device, the skill gap comparison between the firstindividual and the second individual by comparing the first data to thesecond data based at least in part on the preferences identified forperforming the skill gap comparison and the weight assigned for each ofthe plurality of elements of the first data and the second data; andgenerating, by the processing device, a list of one or more skills forwhich there is a skill gap between the first individual and the secondindividual.
 2. The computer-implemented method of claim 1, furthercomprising: updating, by the processing device, the list of one or moreskills in real-time when at least one of new first data associated withthe first individual and new second data associated with the secondindividual are received.
 3. The computer-implemented method of claim 1,wherein the first data associated with the first individual is firstunstructured data, and wherein the second data associated with thesecond individual is second unstructured data.
 4. Thecomputer-implemented method of claim 3, wherein the first unstructureddata associated with the first individual comprise one or more of emaildata, chat history data, education transcript data, calendar data,social media data, role description data, and resume data.
 5. Thecomputer-implemented method of claim 3, wherein the second unstructureddata associated with the second individual comprise one or more of emaildata, chat history data, education transcript data, calendar data,social media data, role description data, and resume data.
 6. Thecomputer-implemented method of claim 1, wherein the plurality ofelements of the first data and the second data comprise words andphrases associated with skills.
 7. The computer-implemented method ofclaim 1, wherein assigning the weight for each of the plurality ofelements of the first data and the second data comprises determining theplurality of elements using a cognitive exploration and content analysisplatform.
 8. The computer-implemented method of claim 1, whereinperforming the skill gap comparison comprises identifying skills for thefirst individual from the first data associated with the firstindividual and identifying skills for the second individual from thesecond data associated with the second individual.
 9. Thecomputer-implemented method of claim 1, further comprising: generating,by the processing device, a list of a plurality of skilled individuals,each of the plurality of skilled individuals having at least one of theskills of the list of the one or more skills for which there is a skillgap between the first individual and the second individual; and ranking,by the processing device, the plurality of skilled individuals based atleast in part on a skill level of the at least one of the skills of thelist of one or more skills.
 10. The computer-implemented method of claim9, wherein the ranking is performed using a retrieve and rank platform.11. The computer-implemented method of claim 1, wherein the secondindividual represents a plurality of individuals, and wherein the seconddata associated with the second individual represents data associatedwith the plurality of individuals.
 12. A system comprising: a memorycomprising computer readable instructions; and a processing device forexecuting the computer readable instructions for performing a method forperforming a skill gap comparison between a first individual and asecond individual, the method comprising: receiving, by the processingdevice, first data associated with the first individual; receiving, bythe processing device, second data associated with the secondindividual; identifying, by the processing device, preferences forperforming the skill gap comparison; assigning, by the processingdevice, a weight for each of a plurality of elements of the first dataand the second data; performing, by the processing device, the skill gapcomparison between the first individual and the second individual bycomparing the first data to the second data based at least in part onthe preferences identified for performing the skill gap comparison andthe weight assigned for each of the plurality of elements of the firstdata and the second data; and generating, by the processing device, alist of one or more skills for which there is a skill gap between thefirst individual and the second individual.
 13. The system of claim 12,wherein the method further comprises: updating, by the processingdevice, the list of one or more skills in real-time when at least one ofnew first data associated with the first individual and new second dataassociated with the second individual are received.
 14. The system ofclaim 12, wherein the first data associated with the first individual isfirst unstructured data, and wherein the second data associated with thesecond individual is second unstructured data.
 15. The system of claim14, wherein the first unstructured data associated with the firstindividual comprise one or more of email data, chat history data,education transcript data, calendar data, social media data, roledescription data, and resume data.
 16. The system of claim 14, whereinthe second unstructured data associated with the second individualcomprise one or more of email data, chat history data, educationtranscript data, calendar data, social media data, role descriptiondata, and resume data.
 17. The system of claim 12, wherein the pluralityof elements of the first data and the second data comprise words andphrases associated with skills.
 18. The system of claim 12, whereinassigning the weight for each of the plurality of elements of the firstdata and the second data comprises determining the plurality of elementsusing a cognitive exploration and content analysis platform.
 19. Thesystem of claim 12, wherein performing the skill gap comparisoncomprises identifying skills for the first individual from the firstdata associated with the first individual and identifying skills for thesecond individual from the second data associated with the secondindividual.
 20. A computer program product comprising: a computerreadable storage medium having program instructions embodied therewith,the program instructions executable by a processing device to cause theprocessing device to perform a method for performing a skill gapcomparison between a first individual and a second individual, themethod comprising: receiving, by the processing device, first dataassociated with the first individual; receiving, by the processingdevice, second data associated with the second individual; identifying,by the processing device, preferences for performing the skill gapcomparison; assigning, by the processing device, a weight for each of aplurality of elements of the first data and the second data; performing,by the processing device, the skill gap comparison between the firstindividual and the second individual by comparing the first data to thesecond data based at least in part on the preferences identified forperforming the skill gap comparison and the weight assigned for each ofthe plurality of elements of the first data and the second data; andgenerating, by the processing device, a list of one or more skills forwhich there is a skill gap between the first individual and the secondindividual.